Algorithm For Reliability Evaluation Research Articles

Reliability modeling and optimization of a two-dimensional system considering performance sharing mechanism

Photovoltaic (PV) power generation systems are increasingly installed on the factory rooftop. The installed PV power generation system exits a two-dimensional structure since the factories are usually designed to be square or rectangular. Motivated by real industry practice, this research proposes a two-dimensional performance sharing reliability model for the factory rooftop PV power generation system, where a common bus exists in each row and across all rows. The component availability is affected by both internal failure and external impacts. The system reliability is the probability that each component can meet its own demand and each row can meet its required demand after performance sharing. To mitigate external impacts, the factory rooftop PV power generation system employs both overarching protection and individual protection measures. We extend the universal generating function (UGF) technique to propose a reliability evaluation algorithm and use the genetic algorithm (GA) to determine optimal protection resource allocation to improve system reliability. Further, the proposed two-dimensional performance sharing reliability model is extended to consider multiple phased-mission. Numerical studies indicate that both expanding common bus capacity and optimizing the protection allocation strategy are effective ways to improve the factory rooftop PV power generation system reliability.

Network reliability of a stochastic flow network by wrapping linear programming models into a Monte-Carlo simulation

A stochastic flow network (SFN) serves as a fundamental framework for real-life network-structured systems and various applications. Network reliability NRd is defined as the probability that an SFN can successfully send at least d units of demand from a source to a terminal. Current analytical algorithms for the network reliability evaluation are classified into an NP-hard problem. This limitation hinders the ability of decision-makers to monitor and manage decisions for an SFN flexibly and immediately. Therefore, this paper develops an algorithm to estimate network reliability by wrapping developed linear programming (LP) models based on minimal paths (MPs) into a Monte-Carlo simulation. The developed LP models present satisfaction of the demand d in the SFN in terms of minimal paths. The effectiveness and efficiency of the proposed algorithm are verified using a series of numerical investigations. Contributions are manifold: (1) an integrated model with the simulation and LP models is provided to estimate network reliability in terms of the MPs, thereby filling a crucial gap in existing research; (2) the scalability and efficiency of the proposed method are shown for the complex SFNs; (3) decision-making capabilities can be provided under real-time reliability predictions.

Reliability Evaluation and Optimization Configuration Method of Network Distribution Side Energy Storage System Based on Machine Vision

To reduce the motor power allocation error and improve voltage weak node conditions, this paper designed a reliability evaluation and optimization configuration method for network distribution side energy storage system based on machine vision. Firstly, the abnormal operation parameters of the energy storage system are collected and transmitted on-site. The operational reliability monitoring data of the distribution network side serves as the foundation for designing the operational reliability evaluation algorithm for the energy storage system on the same distribution network side. This algorithm further enables the optimal configuration of the energy storage system. The experimental comparison results demonstrate that upon implementation of the methods of this paper, the motor power allocation error is less, and the lowest is only 0.17 kW. Meanwhile, the fluctuation is relatively flat, and the range is between 0 kW and 0.46 kW. The improvement of weak voltage nodes is good, the voltage load is significantly decreased, and the minimum voltage load is only 5 kW, which proves that the design method of this paper has a certain application value.

Efficient Anonymous Authentication and Privacy-Preserving Reliability Evaluation for Mobile Crowdsensing in Vehicular Networks

Mobile crowdsensing (MCS) is widely applied in vehicular networks where several sensing vehicles complete the same sensing task. Recently, the privacy and reliability of sensing vehicles have aroused extensive attention of researchers in academia. Although the majority of existing schemes have achieved anonymous authentication with large computation and communication overheads, they do not take the reliability of sensing vehicles into account when selecting sensing vehicles. In this paper, we propose an efficient anonymous authentication and privacy-preserving reliability evaluation (AARE) scheme for MCS, which not only improves the efficiency of mutual authentication but also guarantees the reliability of sensing vehicles. Specifically, an efficient anonymous authentication method is proposed to achieve the anonymous authentication of sensing vehicles. Besides, even if a sensing vehicle passes anonymous authentication, it is difficult to fully guarantee its reliability. Then, a privacy-preserving reliability evaluation algorithm is adopted to evaluate the reliability of sensing vehicles. Meanwhile, in dynamic vehicular networks, the reliability of sensing vehicles is uncertain since there exist many attacks, thus, an accurate reputation update algorithm is designed. Subsequently, the privacy features, computation, and communication overheads in the proposed scheme are analyzed. Comparisons with the existing schemes show that the authentication efficiency of the proposed scheme is increased by 46%-74%, the communication overhead is reduced by 50%-80%, and the accuracy of reputation values of sensing vehicles which submit the reliable/unreliable sensing data is improved/reduced by 16%-22%/67%-74%.

Applying an Artificial Neural network- Developed Collective Animal Behavior Algorithm for seismic reliability evaluation of structure

The seismic design contains considerable uncertainties, which originate from the structural geometries, earthquake motions, analytical models, and material properties. By considering all main uncertainties, reliability analysis is applied estimating the possibility of failure in each of a set of performance requirements. Structural failure localization, quantification, and failure possibility evaluation are principal outputs in the structures reliability evaluation. In this paper, an Artificial Neural Network- Developed Collective Animal Behavior Algorithm is used for reducing the problem complexity needed for reliability investigation and failure detect. In this way, a definite structure is modeled and some failure case are determined. These cases are recognized as train databases for organizing the ANN-DCABA. Therefore, the correlation among structure's response as input and structure's stiffness as output is provided utilizing Artificial Neural Network- Developed Collective Animal Behavior Algorithm. The provided method is so efficient and produces advisable precision in structural failure discovery under a series of ground motions. Besides, for assessing the structure reliability, 5 accidental variables are determined. These are columns’ state of the 1st, 2nd, and 3rd floor, gravity loads, and elasticity modulus. Finally, the Artificial Neural Network- Developed Collective Animal Behavior Algorithm specifies the failure probability of the proposed structure and it can reduce the computational effort required for reliability analysis and damage detection. However, MCS could indicate the failure probability for a given structure; the Artificial Neural Network- Developed Collective Animal Behavior Algorithm helps simulation techniques for receiving an acceptable precision and decrease computational effort.

Air data computer simulation and design credibility assessment considering ADC calculation model

Abstract Air data computer simulation system is a platform for studying aircraft air data system. It can also replace real air data computer and can be used in the experiment of ground integrated avionics system, which greatly reduces the cost and risk of the experiment. However, when the simulation system replaces the real system, whether its reliability, integrity and other indicators can meet the requirements becomes the key to the problem. Based on computer simulation theory and simulation credibility evaluation theory, this paper designs and implements two types of atmospheric data computer simulation systems and evaluates the credibility of the simulation systems. The basic theory of computer simulation and the general process of simulation are expounded, the evaluation theory of simulation credibility is introduced, and the evaluation calculation method of simulation credibility is given. The results show that the highest reliability of the reliability evaluation using the method in this paper reaches 90%, the highest error rate is 0.06%, and the average accuracy, efficiency and complexity of the hundred experiments are 97.31% and 97.00% and 0.154%. The highest reliability of the subjective comprehensive evaluation algorithm for reliability evaluation is 65%, the highest error rate is 0.27%, and the average accuracy, efficiency and complexity of the hundred experiments are 70.59% and 69.74%, and 0.502%. Therefore, the method in this paper not only has high reliability, low error rate, but also has strong comprehensive effectiveness.

Reliability Evaluation and Prediction of Deep Buried Tunnel Based on Similarity Theory and Model Test

Deep buried tunnel has a complex stress environment and large stress level. At present, it is difficult to dynamic monitoring for such tunnels. In order to make the safety evaluation and prediction of tunnel closer to the engineering practice, this paper deduces the tunnel reliability evaluation algorithm. The time-varying reliability of deep tunnel excavation process is analyzed and predicted. Based on the similarity theory, the actual deep tunnel excavation is simulated by indoor model test, the stress and deformation are monitored. The results show that after the tunnel excavation, the reliability of the structure does not decrease gradually, but increases slowly first and then decreases sharply. With the increase of the buried depth of the tunnel, the structural reliability decreases gradually. When the buried depth reaches a certain depth, the structural reliability will decrease rapidly. The influence of different parameters on the structural reliability has different sensitivity. The sensitivity of friction angle is the highest, and the sensitivity of gravity is the lowest. The sensitivity has little effect with the change of tunnel excavation time and tunnel buried depth. The accuracy of this method is verified by the comparative analysis of model box tests.

Uncertain dynamic topology optimization based on the interval reliability evaluation and equivalent static loads (ESLs) algorithm

Uncertain dynamic topology optimization based on the interval reliability evaluation and equivalent static loads (ESLs) algorithm

Reliability Evaluation of Standalone Microgrid Based on Sequential Monte Carlo Simulation Method

In order to analyze the influence of uncertainty and an operation strategy on the reliability of a standalone microgrid, a reliability evaluation method based on a sequential Monte Carlo (SMC) simulation was developed. Here, the duty cycles of a microturbine (MT), the stochastic performance of photovoltaics (PV), and wind turbine generators (WTG) were considered. Moreover, the time-varying load with random fluctuation was modeled. In this method, the available capacity of an energy storage system (ESS) was also comprehensively considered by the SMC simulation. Then, the reliability evaluation framework was established from the perspectives of probability, frequency, and duration, and reliability evaluation algorithms under different operation strategies were formulated. Lastly, the influence of WTG and PV penetration and equipment capacity on the reliability was evaluated in the test system. The results showed that the complementary characteristics of wind and solar and the enhancement of the equipment capacity can both improve the reliability; but, with the increase in the penetration rate of WTG and PV, more ESS capacity is needed to cope with the randomness of WTG and PV. In addition, load shedding minimization strategies can minimize the probability and the number of reductions and achieve optimal reliability, which can provide a reference for the formulation of microgrid operation strategies.

Modular model and algebraic phase algorithm for reliability modelling and evaluation of phased-mission systems with conflicting phase redundancy

Phased-mission systems (PMSs) have been widely used as mission reliability models for many complex systems whose missions can be divided into several phases. In practice, PMSs may have conflicting phase redundancy, that is, a phase task can be performed in more than one phase and redundancy phases can be shared by more than one failed phase. Such PMSs have the following characteristics: (1) the failure of a phase task with redundancy does not directly lead to the failure of the system mission; (2) they have more than one phase level path; and (3) redundancy phases of them have multiple states. This study investigates the reliability modelling and evaluation method of such PMSs with conflicting phase redundancy (PMS-PR). A modular model with new phase states notes was provided to depict the states of phases and deal with the redundant conflicts. A general phase algebraic algorithm is provided to produce all the disjoint phase level paths for the PMS-PR based on the presented model. The mission reliability PMS-PR can be estimated based on disjoint phase level paths. Finally, a simplified telemetry, tracking, and command system under different phase redundancy strategies is analysed to illustrate the effectiveness of the model and algorithm.

Reliability analysis of complex networks based on irredundant subset cut group

This paper presents a unified framework to analyze the performance of a complex network containing diversified link capacities with specified flow requirement in terms of Capacity Related Reliability (CRR). An efficient minimal cutset based methodology is proposed to enumerate irredundant subset cut groups (SCGs) to evaluate flow networks reliability. The proposed approach is a two-step process. The first step requires a prior knowledge of all minimal cutsets of the network along with an enumeration of all irredundant subsets of cutset group (SCG) from a cut matrix to block or allow a prescribed amount of flow. In the second step, the enumerated SCGs can be fed as input to any multi-variable inversion sum-of-disjoint-product (MVI-SDP) based reliability evaluation algorithm to obtain the CRR of the network. The versatility of the proposed approach is that a single framework can be used to evaluate all the reliability measures such as 2-terminal, k-terminal and all-terminal. Various benchmark networks available in literature have been used to analyze the performance of the proposed methodology in terms of complexity and time constraint.

Reliability Evaluation of Nondispatchable Energy Sources in Generation Planning: A Wind Electrical System Case Study

Summary. Generation planning is an important aspect of the probabilistic production simulation (PPS) process for power systems. The inclusion of nondispatchable energy sources in the conventional system needs efficient algorithms for reliability evaluation. Moreover, it is crucial to represent the availability of nondispatchable energy sources with a suitable probability distribution function (PDF) that can be easily integrated with the conventional system. The present work extends the generation reliability to include nondispatchable energy sources in the reliability evaluation methodology. The wind electrical system (WS) is represented using a simple wind speed model based on the normal distribution function. The multistate wind speed model based on the mean and standard deviation of wind speed at a particular site is integrated with the conventional system for reliability study. The proposed fast Fourier transform (FFT)-based method eliminates extensive calculations encountered in the conventional approach due to cumbersome time-domain convolution. The efficacy of the methodology is validated with the case studies using the IEEE RTS-wind system with loss of load probability (LOLP) and expected energy not served (EENS) reliability indices.

Multiservice Reliability Evaluation Algorithm Considering Network Congestion and Regional Failure Based on Petri Net

With the development of complex networks and with increasing service demands, service use is becoming more complex and the composition of services is becoming more complicated. In the XaaS (X as a Service) environment, users only care about the QoE of a service and do not care about the composition process of the service. Therefore, it is important to evaluate the reliability of the entire service. In this article, we use Petri Net as a basis for modeling the composition of services. In addition, we consider the problems of shared resources and common cause faults. Both of these problems can cause network congestion and regional failures. We use distance to assess the effects of regional faults and queuing theory to simulate the network congestion process. Moreover, in the simulation, we verify the impacts of regional failures and network congestion on service reliability. We choose the Tree-Based Search algorithm and the Semi-Markov Model as comparison algorithms. The results of our algorithm are related to service time. Our algorithm can timely reflect the impact of regional failure or network congestion, and it can feedback different evaluation results according to environmental changes. Therefore, our algorithm is more comprehensive and has better performance.

풍력발전기를 고려한 복합전력계통에서의 신뢰도 평가에 관한 연구

In this paper, the probabilistic reliability evaluation algorithm in terms of probabilistic supply adequacy according to the system input of wind turbine generator(WTG) previously proposed by this research team is presented in more detail for a composite power system that also considers the transmission system, and furthermore, the usefulness of the application is verified. In this study, the method was presented in detail through a sample case that can be done manually. Additionally, based on the proposed methodology, a model system similar to the system size of Jeju Island in Korea was assumed, and the reliability evaluation of the composite power system(HL II) considering a large number of WTG in the actual power system size was simulated in various ways, and its usefulness was shown in this paper. Finally, as an application example, the utility of the method developed in this study was verified by showing the possibility in terms of probabilistic reliability of the transmission system expansion planning, which has recently been emphasized more in importance. Therefore, it is expected that the method presented in this study will be practically usable for obtaining the optimal scenario in terms of probabilistic reliability evaluation when conducted the probabilistic transmission system expansion plan considering multiple WTGs.

An improved algorithm for reliability evaluation of flow networks

Many real-world systems such as power transmission and distribution systems, computers and communication, social networks, and so on can be modeled as flow networks which makes the problem of reliability evaluation of such networks of great importance. As transmission time and cost play essential roles in many realistic flow networks, both time and budget constraints are of essential significance and considered in this work. We propose an improved algorithm that computes the exact probability of transmitting d units of data from a source to a destination through one single path within T units of time and the budget of b. The algorithm is illustrated through a benchmark network example. The complexity results are provided. A rather large-sized benchmark, Pan European topology, along with one thousand randomly generated test problems, are used to generate the experimental results, which clearly show the superiority of our proposed algorithms to some existing algorithm in the literature.

AMC-Based Algorithm for Network Reliability Evaluation of a Manufacturing System with Scrapping and Rework

AMC-Based Algorithm for Network Reliability Evaluation of a Manufacturing System with Scrapping and Rework

An Efficient Algorithm for Reliability Evaluation of the Bus Network

The bus network is widely used in industrial automation and avionics systems due to its many advantages. Network reliability is an important indicator of the bus network design and analysis. However, the widely used reliability evaluation method is not capable of dealing with the bus network. In this paper, we model the bus network without redundancy and the bus network with redundancy, propose the algorithms to calculate the two-terminal reliability and the k-terminal reliability of the bus network with redundancy, and verify the effectiveness of the algorithms in three scenarios. The experimental results show that when the reliability of the link reaches 0.9, the two-terminal reliability of the bus network with redundancy of six terminal nodes, eight terminal nodes, and ten terminal nodes is 40.95%, 52.17%, and 61.26% higher than that of the bus network without redundancy, respectively; k-terminal reliability is 61.26%, 74.58%, and 83.32% higher than that of the bus network without redundancy, respectively. The bus network with redundancy increases the communication paths for data exchange between devices, and has higher reliability than the bus network without redundancy. The algorithms proposed in this paper provide an effective solution for the reliability evaluation of the bus network. It perfects the reliability evaluation system of the network with different topology architectures.

A reliability review on electrical collection system of battery energy storage power station

The battery energy storage system is a flexible resource with dual characteristics of source and load. It can be widely used in renewable energy consumption, peak shaving and frequency modulation, virtual power plant, and so on. However, the safety problem of energy storage system used in power system is serious, and it should be given an attention. In addition to being affected by the external operating environment of storage system, the reliability of its internal electrical collection system also plays a decisive role in the safe operation of energy storage power station. Therefore, for the reliability problem of battery energy storage power station, this paper analyzes the collection system structure, reliability model, evaluation algorithm and index system, establishes the single state reliability model of battery module considering derating state, presents a framework of a differentiated two-layer reliability evaluation algorithm for collection system of energy storage power station. This paper’s literature investigation can provide a support for the reliability improvement of energy storage power station.

An extended recursive decomposition algorithm for dynamic seismic reliability evaluation of lifeline networks with dependent component failures

An extended recursive decomposition algorithm (e-RDA) is proposed to evaluate the dynamic seismic reliabilities of the complex and/or large-sized lifeline network systems with dependent component failures. To effectively analyze statistical dependence of failures of system components, multivariate extreme value response distributions of the components and joint occurrence probabilities of the (disjoint) shortest paths and cuts of systems, a multivariate Gumbel Copula is developed and introduced into the original recursive decomposition algorithm (RDA). Based on the established joint occurrence probability formula of the paths and cuts, two techniques that may accelerate convergence of the upper and lower reliability bounds of complex and/or large-sized systems are developed and embedded into the RDA. Illustrative examples are presented to demonstrate the accuracy, effectiveness and use of the extended RDA for the node weight (only node-type components may fail), edge weight (only line-type components may fail) and general weight (both node- and line-type components may fail) lifeline network systems.

Assess the Impacts of Discount Policies on the Reliability of a Stochastic Air Transport Network

In this study, an algorithm for reliability evaluation is proposed in order to assess the discount policy based on its effect on an air transport network. An air transport network is a typical stochastic air transport network (SATN) because its capacity (available seats) is regarded as stochastic. Under different discount policies, the term “reliability” refers to the ability to meet a certain travel demand within a limited budget. To better describe the flow of SATN, the methods of the sum of disjoint products and minimal paths are combined in the proposed algorithm. A reliability analysis is conducted at ranges of budgets and travel demands for a more accurate assessment. The outcomes of this study help the travel agents assess and select an appropriate discount policy, which is one of the important contributions. This study also contributes to enhancing the reliability fluctuation under the impact of multiple discount policies.